Chooch AI is a powerful visual AI platform that can be used to identify, analyze, and monitor any asset, location, or person relevant to the operation, security, or safety of your organization.
Ready for a mind-blowing AI Demo? Chooch AI’s IC2 App for iPhone or Android can tag objects in live video and still images. For instance, it can recognize artwork in a museum and users can click on the tag to learn more about the painting online thanks to artificial intelligence models in the cloud.
Object recognition is a subfield of computer vision, artificial intelligence, and machine learning that seeks to recognize and identify the most prominent objects (i.e., people or things) in a digital image or video with AI models. Image recognition is also a subfield of AI and computer vision that seeks to recognize the high level contents of an image.
If your organization is in search of better, more robust, and reliable security to keep your personnel and assets safe, Chooch AI computer vision is all the solution you need. Computer vision provides broad, full-time, always-on security AI wherever and whenever you need it, utilizing your existing cameras, and running on edge devices to minimize operating costs.
Chooch AI’s computer vision platform can monitor every aspect of a retail operation, be it a minimart or a restaurant — including all front of house customer touchpoints and back of house locations from kitchen to food preparation and storage areas, as well as employee break rooms and office space.
Edge detection is an extremely popular task in fields such as computer vision and image processing. It’s not hard to see why: as humans, we depend on edge detection for tasks such as depth perception and detecting objects in our field of view.
You might know you want to bring computer vision into your organization—but do you know exactly which computer vision use case would offer the most benefit? Image segmentation is a subfield of computer vision that seeks to divide an image into contiguous parts by associating each pixel with a certain category, such as the background or a foreground object.
Detecting unauthorized personnel is a crucial task for any business that needs to protect the safety of their employees and clients, or that stores valuable assets or data on-premises. Human security guards certainly have their uses, but they aren’t without faults, either: they aren’t available around the clock, they can only be present in a single location, and they’re vulnerable to human error (just like the rest of us).
Computer vision, and subfields of computer vision such as object detection and object recognition, can certainly be classified under machine learning, depending on how you build the computer vision model. IBM defines machine learning as“a branch of artificial intelligence (AI) and computer science which focuses on the use of data and algorithms to imitate the way that humans learn, gradually improving its accuracy.”
Knowing how to assess the performance of a pattern recognition model is highly important for a wide variety of tasks in artificial intelligence, machine learning, and computer vision. Below, I’ll discuss some of the most widely used criteria for good pattern recognition systems.